Openings For Data scientist with Financial Crime Domain

Tekskills Inc.; India; Remote; INR 4,200,000 - 6,400,000; Full time

Job summary

Tekskills Inc. is hiring a Senior Data & AI Scientist (Grade E) to lead development of AI/ML solutions for Financial Crime. You will work in multidisciplinary teams, prototype innovative approaches, and deliver production-ready models that drive measurable business value.

You will mentor junior data scientists, shape technical direction, and stay ahead of GenAI and AI governance trends while collaborating with product owners and engineers across the organization.

Qualifications

• 4-10 years of experience in data science with a focus on Financial Crime domain.
• Experience implementing GenAI capabilities, agentic AI, LLMs and cloud deployments.
• Strong proficiency in Python and modern data science tooling.

Responsibilities

• Lead design, development, validation, and deployment of advanced AI/ML models.
• Explore modeling approaches to solve business problems.
• Collect, process, and analyze large datasets from multiple sources.
• Develop experimental models and ML applications using Python and data science tooling.
• Perform complex statistical analysis and translate findings into business decisions.
• Lead small teams in building and maintaining data science products.
• Collaborate with stakeholders to define and deliver analytical solutions.
• Ensure models are scalable, production-ready, and governance-compliant.
• Mentor junior data scientists and support capability development.

Skills

Python

GenAI

Machine Learning

Financial Crime domain

Tools

Cloud deployments

Job description

Hi

We are hiring for Data scientist with Financial Crime

Location: Pan India

Experience: 4- 10 Years

Mandatory Skills: Experience in working for Financial Crime (domain) .To implement Gen AI capabilities or Agentic capabilities , Machine learning, Agentic AI, LLMs, Python, cloud deployments

About the Opportunity

As a Senior Data & AI Scientist (Grade E), you will play a leading role in developing advanced machine learning, AI, and analytics solutions that solve complex business challenges. You will work in multidisciplinary teams to explore problem statements, experiment with innovative approaches, and deliver production-ready solutions that create measurable business value. You will also provide technical leadership and coaching to junior data scientists while helping shape the technical direction of the team.

Key Responsibilities

• Lead the design, development, validation, and deployment of advanced AI and Machine Learning models.


• Explore and evaluate different modelling approaches to solve business problems.


• Collect, process, and analyse large and complex datasets from multiple sources.


• Develop experimental models and machine learning applications using Python and modern data science tooling.


• Perform complex statistical analysis and translate findings into actionable business recommendations.


• Lead small teams in the development, maintenance, and enhancement of data science products.


• Collaborate with business stakeholders, product owners, engineers, and analysts to define and deliver analytical solutions.


• Ensure models are scalable, production-ready, and compliant with governance standards.


• Mentor and coach junior data scientists and support capability development across the team.


• Stay informed on emerging AI, GenAI, machine learning, and data science trends and identify opportunities to apply them within Lloyds Banking Group.

Required Skills & Experience

• Strong experience in Machine Learning, Predictive Analytics, Statistical Modelling, and AI.


• Expertise in Python and associated data science libraries.


• Experience in feature engineering, model selection, validation frameworks, and model performance evaluation.


• Strong understanding of supervised and unsupervised learning techniques.


• Experience working with cloud platforms, preferably Google Cloud Platform (GCP).


• Ability to communicate complex analytical findings to both technical and non-technical audiences.


• Experience leading projects and mentoring team members.


• Strong stakeholder management and collaboration skills.

Leadership Expectations

• Act as a technical leader within projects and workstreams.


• Drive adoption of best practices across Data Science and AI delivery.


• Support capability growth through coaching, mentoring, and knowledge sharing.


• Foster a culture of innovation, experimentation, and continuous improvement.

Typical Outcomes

• Industrialised AI and Machine Learning solutions delivering measurable business impact.


• Improved decision-making through advanced analytics and predictive modelling.


• Enhanced team capability through mentoring and technical leadership.


• Delivery of data science products aligned with governance, risk, and ethical AI standards.